September 2014
Intermediate to advanced
512 pages
12h 39m
English
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Writing massively parallel code for heterogeneous platforms with OpenCL
In the previous recipe, we introduced CUDA, a proprietary GPGPU framework created by NVIDIA Corporation. In this recipe, we present OpenCL, an alternative open framework initiated by Apple in 2008. It is now adopted by mainstream companies including Intel, NVIDIA, AMD, Qualcomm, ARM, and others. These companies are regrouped within the non-profit technology consortium Khronos Group (which also maintains the OpenGL real-time rendering specification). Programs written in OpenCL can run on GPUs and CPUs (heterogeneous computing).
Tip
CUDA and OpenCL are relatively similar in terms of concepts, syntax, and features. CUDA sometimes leads to slightly higher performance, since its ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.